Demo Data from EDBT 2026 / reviewers in the wild / expert
Max Seiden
dblp:280/0987
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Data integration and cleaning · 50% Query processing and optimization · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning › data warehouse
cloud data warehouse |
0.6 | 1 | 2022 | Sigma Workbook: A Spreadsheet for Cloud Data Warehouses · Proc. VLDB Endow. 2022 |
Cloud and datacenter computing › cloud data management
cloud data warehouse |
0.2 | 1 | 2022 | Sigma Workbook: A Spreadsheet for Cloud Data Warehouses · Proc. VLDB Endow. 2022 |
Methods — techniques the papers use, named apart from their topics
direct manipulation · 1.1SQL generation · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Sigma Workbook: A Spreadsheet for Cloud Data WarehousesabstractCloud data warehouses (CDWs) bring large-scale data and compute power closer to users in enterprises. However, existing tools for analyzing data in CDWs are either limited in ad-hoc transformations or difficult to use for business users. Here we introduce Sigma Workbook, a new interactive system that enables business users to easily perform visual analysis of data in CDWs at scale. For this, Sigma Workbook provides an accessible spreadsheet-like interface for analysis through direct manipulation. Sigma Workbook dynamically constructs matching SQL queries from user interactions, building on the versatility and expressivity of SQL. Constructed queries are directly executed on CDWs, leveraging the superior characteristics of the new generation CDWs, including scalability. We demonstrate Sigma Workbook through 3 real-life use cases---cohort analysis, sessionization, and data augmentation---and underline Workbook's ease of use, scalability, and expressivity. James Gale, Max Seiden, Deepanshu Utkarsh, Jason Frantz, Rob Woollen, Çagatay Demiralp |
Proc. VLDB Endow. | 2 |